Continental, NVIDIA partner
Alliance to enable worldwide production of AI self-driving cars
Graphics cards maker NVIDIA and Continental, an automotive technology company, have partnered to create top-to-bottom AI self-driving vehicle systems built on the NVIDIA Drive platform, with a planned market introduction starting in 2021.
The partnership will enable the production of AI computer systems that scale from automated Level 2 features through full Level 5 self-driving capabilities, where the vehicle has no steering wheel or pedals.
Dedicated engineering teams from each company will work together to develop self-driving solutions based on the NVIDIA Drive platform - which includes NVIDIA Drive Xavier, the world's highest performance system-on-a-chip, as well as the NVIDIA Drive OS (operating system) and Drive AV (autonomous vehicle) software stacks.
The solutions will utilise Continental's experience in system and software engineering for ASIL-D rated safety - the highest rating level - and integrate a range of Continental sensor technologies, including radar, camera and high-resolution 3D lidar.
"The vehicle of the future will be a sensing, planning and acting computer on wheels. The complexity of autonomous driving requires nothing less than the full computational horsepower of an AI supercomputer," said Dr. Elmar Degenhart, CEO of Continental. "Together with the performance and flexibility of NVIDIA's AI self-driving solution, from the cloud to the car we will achieve new levels of safety, comfort and personalisation for future vehicles."
Jensen Huang, founder and CEO of NVIDIA, said: "We now have all the key elements in place to take AI self-driving cars from development to mass production. Our newly arrived DRIVE Xavier processor, extensive NVIDIA Drive software, and cloud-to-car approach for testing, validation and functional safety, combined with Continental's expertise and global reach, will bring autonomous cars to the world."
As the brain of the Continental system, NVIDIA Drive Xavier can deliver 30 trillion operations per second (TOPS) for deep learning, while consuming only 30 watts of energy.